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Background
Antidepressant medication is commonly used to treat depression. However, many patients do not respond to the first medication prescribed and improvements in symptoms are generally only detectable by clinicians 4–6 weeks after the medication has been initiated. As a result, there is often a long delay between the decision to initiate an antidepressant medication and the identification of an effective treatment regimen.
Previous work has demonstrated that antidepressant medications alter subtle measures of affective cognition in depressed patients, such as the appraisal of facial expression. Furthermore, these cognitive effects of antidepressants are apparent early in the course of treatment and can also predict later clinical response. This trial will assess whether an electronic test of affective cognition and symptoms (the Predicting Response to Depression Treatment Test; PReDicT Test) can be used to guide antidepressant treatment in depressed patients and, therefore, hasten treatment response compared to a control group of patients treated as usual.
Methods/design
The study is a randomised, two-arm, multi-centre, open-label, clinical investigation of a medical device, the PReDicT Test. It will be conducted in five European countries (UK, France, Spain, Germany and the Netherlands) in depressed patients who are commencing antidepressant medication. Patients will be randomised to treatment guided by the PReDicT Test (PReDicT arm) or to Treatment as Usual (TaU arm). Patients in the TaU arm will be treated as per current standard guidelines in their particular country. Patients in the PReDicT arm will complete the PReDicT Test after 1 (and if necessary, 2) weeks of treatment. If the test indicates non-response to the treatment, physicians will be advised to immediately alter the patient’s antidepressant therapy by dose escalation or switching to another compound. The primary outcome of the study is the proportion of patients showing a clinical response (defined as 50% or greater decrease in baseline scores of depressionmeasured using the Quick Inventory of Depressive Symptoms – Self-Rated questionnaire) at week 8. Health economic and acceptability data will also be collected and analysed.
Discussion
This trial will test the clinical efficacy, cost-effectiveness and acceptability of using the novel PReDicT Test to guide antidepressant treatment selection in depressed patients.
Trial registration
ClinicalTrials.gov, ID: NCT02790970. Registered on 30 March 2016.
Quantifying protein densities on cell membranes using super-resolution optical fluctuation imaging
(2017)
Quantitative approaches for characterizing molecular organization of cell membrane molecules under physiological and pathological conditions profit from recently developed super-resolution imaging techniques. Current tools employ statistical algorithms to determine clusters of molecules based on single-molecule localization microscopy (SMLM) data. These approaches are limited by the ability of SMLM techniques to identify and localize molecules in densely populated areas and experimental conditions of sample preparation and image acquisition. We have developed a robust, model-free, quantitative clustering analysis to determine the distribution of membrane molecules that excels in densely labeled areas and is tolerant to various experimental conditions, i.e. multiple-blinking or high blinking rates. The method is based on a TIRF microscope followed by a super-resolution optical fluctuation imaging (SOFI) analysis. The effectiveness and robustness of the method is validated using simulated and experimental data investigating nanoscale distribution of CD4 glycoprotein mutants in the plasma membrane of T cells.
We theoretically investigate the propagation of heat currents in a three-terminal quantum dot engine. Electron–electron interactions introduce state-dependent processes which can be resolved by energy-dependent tunneling rates. We identify the relevant transitions which define the operation of the system as a thermal transistor or a thermal diode. In the former case, thermal-induced charge fluctuations in the gate dot modify the thermal currents in the conductor with suppressed heat injection, resulting in huge amplification factors and the possible gating with arbitrarily low energy cost. In the latter case, enhanced correlations of the state-selective tunneling transitions redistribute heat flows giving high rectification coefficients and the unexpected cooling of one conductor terminal by heating the other one. We propose quantum dot arrays as a possible way to achieve the extreme tunneling asymmetries required for the different operations.
A search for new phenomena in final states characterized by high jet multiplicity, an isolated lepton (electron or muon) and either zero or at least three \(b\)-tagged jets is presented. The search uses 36.1 fb\(^{−1}\) of \(\sqrt{s}=13\) TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider in 2015 and 2016. The dominant sources of background are estimated using parameterized extrapolations, based on observables at medium jet multiplicity, to predict the \(b\)-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. No significant excess over the Standard Model expectation is observed and 95% confidence-level limits are extracted constraining four simplified models of \(R\)-parity-violating supersymmetry that feature either gluino or top-squark pair production. The exclusion limits reach as high as 2.1 TeV in gluino mass and 1.2 TeV in top-squark mass in the models considered. In addition, an upper limit is set on the cross-section for Standard Model \(t\overline{t}t\overline{t}\) production of 60 fb (6.5 × the Standard Model prediction) at 95% confidence level. Finally, model-independent limits are set on the contribution from new phenomena to the signal-region yields.
Background
Obsessive-Compulsive Disorder (OCD) is a common and chronic disorder in which a person has uncontrollable, reoccurring thoughts and behaviours. It is a complex genetic condition and, in case of early onset (EO), the patients manifest a more severe phenotype, and an increased heritability. Large (>500 kb) copy number variations (CNVs) previously associated with autism and schizophrenia have been reported in OCD. Recently, rare CNVs smaller than 500 kb overlapping risk loci for other neurodevelopmental conditions have also been reported in OCD, stressing the importance of examining CNVs of any size range. The aim of this study was to further investigate the role of rare and small CNVs in the aetiology of EO-OCD.
Methods
We performed high-resolution chromosomal microarray analysis in 121 paediatric OCD patients and in 124 random controls to identify rare CNVs (>50 kb) which might contribute to EO-OCD.
Results
The frequencies and the size of the observed rare CNVs in the patients did not differ from the controls. However, we observed a significantly higher frequency of rare CNVs affecting brain related genes, especially deletions, in the patients (OR = 1.98, 95% CI 1.02–3.84; OR = 3.61, 95% CI 1.14–11.41, respectively). Similarly, enrichment-analysis of CNVs gene content, performed with three independent methods, confirmed significant clustering of predefined genes involved in synaptic/brain related functional pathways in the patients but not in the controls. In two patients we detected \(de-novo\) CNVs encompassing genes previously associated with different neurodevelopmental disorders \(\textit{NRXN1, ANKS1B, UHRF1BP1}\)).
Conclusions
Our results further strengthen the role of small rare CNVs, particularly deletions, as susceptibility factors for paediatric OCD.
A search for strongly produced supersymmetric particles using signatures involving multiple energetic jets and either two isolated same-sign leptons (\(e\) or \(µ\)), or at least three isolated leptons, is presented. The analysis relies on the identification of \(b\)-jets and high missing transverse momentum to achieve good sensitivity. A data sample of proton-proton collisions at \(\sqrt{s} = 13\) TeV recorded with the ATLAS detector at the Large Hadron Collider in 2015 and 2016, corresponding to a total integrated luminosity of 36.1 fb\(^{−1}\), is used for the search. No significant excess over the Standard Model prediction is observed. The results are interpreted in several simplified supersymmetric models featuring \(R\)-parity conservation or \(R\)-parity violation, extending the exclusion limits from previous searches. In models considering gluino pair production, gluino masses are excluded up to 1.87 TeV at 95% confidence level. When bottom squarks are pair-produced and decay to a chargino and a top quark, models with bottom squark masses below 700 GeV and light neutralinos are excluded at 95% confidence level. In addition, model-independent limits are set on a possible contribution of new phenomena to the signal region yields.
Low-energy spin excitations in any long-range ordered magnetic system in the absence of magnetocrystalline anisotropy are gapless Goldstone modes emanating from the ordering wave vectors. In helimagnets, these modes hybridize into the so-called helimagnon excitations. Here we employ neutron spectroscopy supported by theoretical calculations to investigate the magnetic excitation spectrum of the isotropic Heisenberg helimagnet \({ZnCr_2Se_4}\) with a cubic spinel structure, in which spin\(-3/2\) magnetic \({Cr^{3+}}\) ions are arranged in a geometrically frustrated pyrochlore sublattice. Apart from the conventional Goldstone mode emanating from the \((0~ 0~ {q_h})\) ordering vector, low-energy magnetic excitations in the single-domain proper-screw spiral phase show soft helimagnon modes with a small energy gap of \({∼0.17~ meV}\), emerging from two orthogonal wave vectors \(({q_h}~ 0~ 0)\) and \({(0~ {q_h}~ 0)}\) where no magnetic Bragg peaks are present. We term them pseudo-Goldstone magnons, as they appear gapless within linear spinwave theory and only acquire a finite gap due to higher-order quantum-fluctuation corrections. Our results are likely universal for a broad class of symmetric helimagnets, opening up a new way of studying weak magnon-magnon interactions with accessible spectroscopic methods.
The top-quark mass is measured in the all-hadronic top-antitop quark decay channel using proton-proton collisions at a centre-of-mass energy of \(\sqrt{s}=8\) TeV with the ATLAS detector at the CERN Large Hadron Collider. The data set used in the analysis corresponds to an integrated luminosity of 20.2 fb\(^{−1}\). The large multi-jet background is modelled using a data-driven method. The top-quark mass is obtained from template fits to the ratio of the three-jet to the dijet mass. The three-jet mass is obtained from the three jets assigned to the top quark decay. From these three jets the dijet mass is obtained using the two jets assigned to the W boson decay. The top-quark mass is measured to be 173.72 ± 0.55 (stat.) ± 1.01 (syst.) GeV.
This article presents searches for the \({Zγ}\) decay of the Higgs boson and for narrow high-mass resonances decaying to \(Z\)γ, exploiting \(Z\) boson decays to pairs of electrons or muons. The data analysis uses 36.1 fb\(^{−1}\) of \({pp}\) collisions at \(\sqrt{s}=13\) recorded by the ATLAS detector at the CERN Large Hadron Collider. The data are found to be consistent with the expected Standard Model background. The observed (expected — assuming Standard Model \({pp} → H → {Z}γ\) production and decay) upper limit on the production cross section times the branching ratio for \({pp} → H → {Z}γ\) is 6.6. (5.2) times the Standard Model prediction at the 95% confidence level for a Higgs boson mass of 125.09 GeV. In addition, upper limits are set on the production cross section times the branching ratio as a function of the mass of a narrow resonance between 250 GeV and 2.4 TeV, assuming spin-0 resonances produced via gluon-gluon fusion, and spin-2 resonances produced via gluon-gluon or quark-antiquark initial states. For high-mass spin-0 resonances, the observed (expected) limits vary between 88 fb (61 fb) and 2.8 fb (2.7 fb) for the mass range from 250 GeV to 2.4 TeV at the 95% confidence level.
Objectives: Chronic recurrent multifocal osteomyelitis (CRMO), the most severe form of chronic nonbacterial osteomyelitis (CNO), is an autoinflammatory bone disorder. In the absence of diagnostic criteria or biomarkers, CNO/CRMO remains a diagnosis of exclusion. The aim of this study was to identify biomarkers for diagnosing multifocal disease (CRMO).
Study design: Sera from 71 pediatric CRMO patients, 11 patients with osteoarticular infections, 62 patients with juvenile idiopathic arthritis (JIA), 7 patients with para-infectious or reactive arthritis, and 43 patients with acute leukemia or lymphoma, as well as 59 healthy individuals were collected. Multiplex analysis of 18 inflammation- and/or bone remodeling-associated serum proteins was performed. Statistical analysis included univariate ANOVA, discriminant analysis, univariate receiver operating characteristic (ROC) analysis, and logistic regression analyses.
Results: For 14 of 18 blood serum proteins, significant differences were determined between CRMO patients, at least one alternative diagnosis, or healthy controls. Multi-component discriminant analysis delivered five biomarkers (IL-6, CCL11/eotaxin, CCL5/RANTES, collagen Iα, sIL-2R) for the diagnosis of CRMO. ROC analysis allowed further reduction to a core set of 2 biomarkers (CCL11/eotaxin, IL-6) that are sufficient to discern between CRMO, healthy controls, and alternative diagnoses.
Conclusion: Serum biomarkers CCL11/eotaxin and IL-6 differentiate between patients with CRMO, healthy controls, and alternative diagnoses (leukemia and lymphoma, osteoarticular infections, para-infectious arthritis, and JIA). Easily accessible biomarkers may aid in diagnosing CRMO. Further studies testing biomarkers in larger unrelated cohorts are warranted.